PCB Defect Detection Using Image Processing for Component Analysis

Abstract

Printed Circuit Boards (PCBs) are fundamental components in modern electronic systems, serving as the backbone for electrical connectivity and mechanical support. Ensuring their quality is critical, as defects can lead to malfunctioning or complete failure of electronic devices. This paper presents an automated PCB defect detection system using image processing techniques. The proposed system compares real-time PCB images with reference images to detect missing, damaged, or misaligned components. Techniques such as pre-processing, feature extraction, edge detection, and structural similarity analysis are employed to improve detection accuracy. The system minimizes manual inspection effort, reduces human error, and enhances efficiency. Experimental evaluation demonstrates the effectiveness of the system in identifying defects with high reliability.